Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/alleneubank/claude-code/helpgit clone --depth 1 https://github.com/alleneubank/claude-codeWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00006 | $0.00437 |
| Opus 5 | $0.00003 | $0.00218 |
| Sonnet 5 | $0.00001 | $0.00087 |
| Haiku 4.5 | $0.00001 | $0.00044 |
Grade A, and why
help scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Ralph Reviewed - Help
Ralph Reviewed is an iterative development loop with Codex review gates.
How It Works
- You start a loop with
/ralph-reviewed:ralph-loop "your task" - Claude works on the task iteratively
- When Claude claims completion, Codex reviews the work
- If approved: loop ends
- If rejected: Claude gets feedback and continues
Commands
/ralph-reviewed:ralph-loop
Start an iterative loop with review gates.
Usage:
/ralph-reviewed:ralph-loop "Your task description" [options]
Options:
--max-iterations <n>- Max work iterations before auto-stop (default: 30)--max-reviews <n>- Max review cycles before force-complete (default: --max-iterations)--no-review- Disable Codex review gate--debug- Enable debug logging
Completion: The agent runs .rl/rl done when finished, or .rl/rl done --blocked if stuck.
Examples:
/ralph-reviewed:ralph-loop "Build a REST API with CRUD for todos. Include tests." --max-iterations 30
/ralph-reviewed:ralph-loop "Fix the authentication bug in src/auth.ts. Tests must pass." --max-reviews 2
/ralph-reviewed:cancel-ralph
Cancel the active loop immediately.
/ralph-reviewed:help
Show this help message.
Troubleshooting
Loop won't stop:
- Use
/ralph-reviewed:cancel-ralphto force stop - Ensure the agent ran
.rl/rl donebefore stopping
Codex not reviewing:
- Ensure
codexCLI is installed and authenticated - Check that
--no-reviewis not set
Too many review cycles:
- After max reviews, loop completes with a warning
- Reduce scope or clarify requirements in the task
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 64 lines · 6 tokens per session scan A 2410ed6f91cd
help is a command published in the GitHub repository alleneubank/claude-code (52 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 6 tokens to every session and 437 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.